Hello,
In my ongoing quest of improving NeoRL to produce a generic intelligent reinforcement learning agent, I created a demo I would like to share. It’s a simple demo, but still interesting in my opinion.
The agent receives 1D vision data (since the game is 2D), and must drive a car around a thin track. This is essentially a “thread the needle” task, where the AI requires relatively precise control in order to obtain reward.
As a human, I was not able to make it as far as the AI did. The AI almost completed the entire track, I was only able to make it about half-way. It looks easy, but it’s not!
Training time: About 2 minutes.
Here is a video of the car being controlled by NeoRL:
Until next time!
Very impressive, as usual. As for the sensory input being 1D, is distance also encoded in the rays? If so, that would make input 2D as for my understanding. Also, I wonder how you encode those rays into a SDR exactly. Do you mind elaborating a bit on how you designed that?